Identifying plant taxa that honey bees (Apis mellifera) forage upon is of great apicultural interest, but traditional methods are labor intensive and may lack resolution. Here we evaluate a high-throughput genetic barcoding approach to characterize trap-collected pollen from multiple North Dakota apiaries across multiple years. We used the Illumina MiSeq platform to generate sequence scaffolds from non-overlapping 300-bp paired-end sequencing reads of the ribosomal internal transcribed spacers (ITS). Full-length sequence scaffolds represented ~530 bp of ITS sequence after adapter trimming, drawn from the 5’ of ITS1 and the 3’ of ITS2, while skipping the uninformative 5.8S region. Operational taxonomic units (OTUs) were picked from scaffolds clustered at 97% identity, searched by BLAST against the nt database, and given taxonomic assignments using the paired-read lowest common ancestor approach. Taxonomic assignments and quantitative patterns were consistent with known plant distributions, phenology, and observational reports of pollen foraging, but revealed an unexpected contribution from non-crop graminoids and wetland plants. The mean number of plant species assignments per sample was 23.0 (+/- 5.5) and the mean species diversity (effective number of equally abundant species) was 3.3 (+/- 1.2). Bray-Curtis similarities showed good agreement among samples from the same apiary and sampling date. Rarefaction plots indicated that fewer than 50,000 reads are typically needed to characterize pollen samples of this complexity. Our results show that a pre-compiled, curated reference database is not essential for genus-level assignments, but species-level assignments are hindered by database gaps, reference length variation, and probable errors in the taxonomic assignment, requiring post-hoc evaluation. Although the effective per-sample yield achieved using custom MiSeq amplicon primers was less than the machine maximum, primarily due to lower “read2” quality, further protocol optimization and/or a modest reduction in multiplex scale should offset this difficulty. As small quantities of pollen are sufficient for amplification, our approach might be extendable to other questions or species for which large pollen samples are not available.
","language":"English","publisher":"PLoS","publisherLocation":"San Francisco","doi":"10.1371/journal.pone.0145365","usgsCitation":"Cornman, R.S., Otto, C., Iwanowicz, D.D., and Pettis, J.S., 2015, Taxonomic characterization of honey bee (Apis mellifera) pollen foraging based on non-overlapping paired-end sequencing of nuclear ribosomal loci: PLoS ONE, v. 10, no. 12, p. 1-26, https://doi.org/10.1371/journal.pone.0145365.","productDescription":"26 p.","startPage":"1","endPage":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067288","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471557,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0145365","text":"Publisher Index Page"},{"id":313041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.96484375,\n 46.84704298339389\n ],\n [\n -98.96484375,\n 47.44852243794931\n ],\n [\n -97.83599853515625,\n 47.44852243794931\n ],\n [\n -97.83599853515625,\n 46.84704298339389\n ],\n [\n -98.96484375,\n 46.84704298339389\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-23","publicationStatus":"PW","scienceBaseUri":"56850061e4b0a04ef4933751","contributors":{"authors":[{"text":"Cornman, Robert S. 0000-0001-9511-2192 rcornman@usgs.gov","orcid":"https://orcid.org/0000-0001-9511-2192","contributorId":5356,"corporation":false,"usgs":true,"family":"Cornman","given":"Robert","email":"rcornman@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":583636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":583637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594 diwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":2253,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah","email":"diwanowicz@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":583638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pettis, Jeffery S","contributorId":150913,"corporation":false,"usgs":false,"family":"Pettis","given":"Jeffery","email":"","middleInitial":"S","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":583639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159801,"text":"ds973 - 2015 - Chemical concentrations and instantaneous loads, Green River to the Lower Duwamish Waterway near Seattle, Washington, 2013–15","interactions":[],"lastModifiedDate":"2015-12-28T12:34:29","indexId":"ds973","displayToPublicDate":"2015-12-23T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"973","title":"Chemical concentrations and instantaneous loads, Green River to the Lower Duwamish Waterway near Seattle, Washington, 2013–15","docAbstract":"In November 2013, U.S. Geological Survey streamgaging equipment was installed at a historical water-quality station on the Duwamish River, Washington, within the tidal influence at river kilometer 16.7 (U.S. Geological Survey site 12113390; Duwamish River at Golf Course at Tukwila, WA). Publicly available, real-time continuous data includes river streamflow, stream velocity, and turbidity. Between November 2013 and March 2015, the U.S. Geological Survey collected representative samples of water, suspended sediment, or bed sediment from the streamgaging station during 28 periods of differing flow conditions. Samples were analyzed by Washington-State-accredited laboratories for a large suite of compounds, including metals, dioxins/furans, semivolatile compounds including polycyclic aromatic hydrocarbons, pesticides, butytins, polychlorinated biphenyl (PCB) Aroclors and the 209 PCB congeners, volatile organic compounds, hexavalent chromium, and total and dissolved organic carbon. Metals, PCB congeners, and dioxins/furans were frequently detected in unfiltered-water samples, and concentrations typically increased with increasing suspended-sediment concentrations. Chemical concentrations in suspendedsediment samples were variable between sampling periods. The highest concentrations of many chemicals in suspended sediment were measured during summer and early autumn storm periods.
\nMedian chemical concentrations in suspended-sediment samples were greater than median chemical concentrations in fine bed sediment (less than 62.5 µm) samples, which were greater than median chemical concentrations in paired bulk bed sediment (less than 2 mm) samples. Suspended-sediment concentration, sediment particle-size distribution, and general water-quality parameters were measured concurrent with the chemistry sampling. From this discrete data, combined with the continuous streamflow record, estimates of instantaneous sediment and chemical loads from the Green River to the Lower Duwamish Waterway were calculated. For most compounds, loads were higher during storms than during baseline conditions because of high streamflow and high chemical concentrations. The highest loads occurred during dam releases (periods when stored runoff from a prior storm is released from the Howard Hanson Dam into the upper Green River) because of the high river streamflow and high suspended-sediment concentration, even when chemical concentrations were lower than concentrations measured during storm events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds973","collaboration":"Prepared in cooperation with the Washington State Department of Ecology","usgsCitation":"Conn, K.E., Black, R.W., Vanderpool-Kimura, A.M., Foreman, J.R., Peterson, N.T., Senter, C.A., and Sissel, S.K., 2015, Chemical concentrations and instantaneous loads, Green River to the Lower Duwamish Waterway near Seattle, Washington, 2013–15: U.S. Geological Survey Data Series 973, 46 p., https://dx.doi.org/10.3133/ds973.","productDescription":"Report: vii, 46 p.; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065963","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":312810,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0973/ds973.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 973 PDF"},{"id":312811,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0973/coverthb.jpg"},{"id":312812,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0973/ds973_appendixa.xlsx","text":"Appendix A","size":"846 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 973 Appendix A XLSX"}],"country":"United States","state":"Washington","otherGeospatial":"Green River, Lower Duwamish Waterway","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.4,\n 47.4\n ],\n [\n -122.4,\n 47.6\n ],\n [\n -122.2,\n 47.6\n ],\n [\n -122.2,\n 47.4\n ],\n [\n -122.4,\n 47.4\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
The hydrogeology of the Owego-Apalachin Elementary School geothermal fields, which penetrate saline water and methane in fractured upper Devonian age bedrock in the Owego Creek valley, south-central New York, was characterized through the analysis of drilling and geophysical logs, water-level monitoring data, and specific-depth water samples. Hydrogeologic insights gained during the study proved beneficial for the design of the geothermal drilling program and protection of the overlying aquifer during construction, and may be useful for the development of future geothermal fields and other energy-related activities, such as drilling for oil and natural gas in similar fractured-bedrock settings.
\nThe southwest geothermal field consists of 204 closed-loop wells that penetrate a major saline water-bearing zone associated with bedding-plane fractures near the middle of an interbedded sandstone and shale interval at depths of 238 to 263 feet below land surface (ft bls). The northeast geothermal field consists of 80 closed-loop wells that penetrate a major saline water-bearing zone associated with bedding-plane fractures near the base of the interbedded sandstone and shale interval at depths of 303 to 323 ft bls.
\nTransmissivity estimates for the major saline water-bearing fractured zones range from 735 to 3,400 feet squared per day. The saline water-bearing zone in the southwest field is hydraulically connected over a horizontal distance of at least 350 feet. The hydraulic connection between subhorizontal, stacked bedding-plane fractures is limited by the number and transmissivity of interspersed higher angle fractures; locally, greater stratigraphic separation results in reduced connectivity to a greater degree than does horizontal distance.
\nThe specific conductance of the saline water from the shallower fractured zone in the southwest field was about 16,000 microsiemens per centimeter at 25 degrees Celsius (μS/cm at 25°C), and that from the fractured zone in the northeast field was about 65,000 μS/cm at 25°C. The saline waters were characterized by a chemical composition similar to that of deep formation brines collected from oil and gas wells in the Appalachian Basin. About 40 percent of the geothermal wells discharged methane gas to land surface during and (or) following drilling. Sandstone beds at depths of 348 to 378 ft bls are the likely source of the methane gas, which was determined to be early thermogenic in origin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155155","usgsCitation":"Williams, J.H., and Kappel, W.M., 2015, Hydrogeology of the Owego-Apalachin Elementary School geothermal fields, Tioga County, New York: U.S. Geological Survey Scientific Investigations Report 2015–5155, 29 p., https://dx.doi.org/10.3133/sir20155155.","productDescription":"Report: vii, 29 p.; 4 Appendixes","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066669","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":312655,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix02.xlsx","text":"Appendix 2","size":"23 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5155","linkHelpText":"Location, construction, and hydrogeologic information for selected boreholes and wells"},{"id":312729,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix01.m4v","text":"Appendix 1 (Low Resolution)","size":"5.12 MB","description":"SIR 2015-5155","linkHelpText":"Video of local news report about methane fire during drilling of borehole A9"},{"id":312730,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix04.m4v","text":"Appendix 4 (Low Resolution)","size":"35.6 MB","description":"SIR 2015-5155","linkHelpText":"Video of unloading of methane gas and water from borehole A12"},{"id":312654,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix01.mp4","text":"Appendix 1 (High Resolution)","size":"10.2 MB","description":"SIR 2015-5155","linkHelpText":"Video of local news report about methane fire during drilling of borehole A9"},{"id":312657,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix04.mp4","text":"Appendix 4 (High Resolution)","size":"49.8 MB","description":"SIR 2015-5155","linkHelpText":"Video of unloading of methane gas and water from borehole A12"},{"id":312652,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155.pdf","text":"Report","size":"7.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5155"},{"id":312651,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5155/images/coverthb.jpg"},{"id":312656,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5155/sir20155155_appendix03.xlsx","text":"Appendix 3","size":"15 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5155","linkHelpText":"Field and laboratory chemical analyses from boreholes A9 and Q1"}],"country":"United States","state":"New York","county":"Tioga County","city":"Owego","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-76.1258,42.4107],[-76.123,42.3825],[-76.1267,42.382],[-76.1247,42.3652],[-76.1173,42.3653],[-76.1172,42.3576],[-76.1129,42.3571],[-76.1122,42.348],[-76.1084,42.3476],[-76.1071,42.3376],[-76.1195,42.3375],[-76.1194,42.3275],[-76.1139,42.3276],[-76.1144,42.3185],[-76.1069,42.3181],[-76.1069,42.3094],[-76.1025,42.309],[-76.1031,42.3026],[-76.0981,42.3022],[-76.0993,42.2927],[-76.1073,42.2931],[-76.1079,42.2876],[-76.1017,42.2877],[-76.1023,42.2808],[-76.088,42.2804],[-76.0892,42.275],[-76.0842,42.2746],[-76.0842,42.2664],[-76.0798,42.2659],[-76.0791,42.2587],[-76.0965,42.2595],[-76.0964,42.25],[-76.0909,42.25],[-76.0921,42.2459],[-76.0859,42.2459],[-76.0858,42.2414],[-76.092,42.2414],[-76.0913,42.2337],[-76.0845,42.2341],[-76.0857,42.2282],[-76.082,42.2273],[-76.0801,42.2183],[-76.0862,42.2178],[-76.085,42.2119],[-76.0912,42.2123],[-76.0899,42.2064],[-76.083,42.2069],[-76.0823,42.1928],[-76.0885,42.1928],[-76.0885,42.1869],[-76.1151,42.1858],[-76.1123,42.1509],[-76.106,41.9991],[-76.1165,41.9992],[-76.1467,41.9991],[-76.3826,41.9989],[-76.466,41.9999],[-76.5229,42.0005],[-76.5531,42.0008],[-76.5618,42.0009],[-76.5675,42.0121],[-76.5632,42.0153],[-76.544,42.0536],[-76.5538,42.0885],[-76.5581,42.1239],[-76.5594,42.1312],[-76.5539,42.1312],[-76.5597,42.1507],[-76.5598,42.1557],[-76.5344,42.1568],[-76.5377,42.2504],[-76.5382,42.2817],[-76.4731,42.2808],[-76.4734,42.2631],[-76.417,42.2631],[-76.4153,42.3194],[-76.3507,42.3181],[-76.35,42.3085],[-76.2898,42.308],[-76.2891,42.2962],[-76.25,42.2964],[-76.2514,42.3073],[-76.2497,42.3241],[-76.2473,42.336],[-76.2425,42.3446],[-76.2382,42.3542],[-76.2402,42.3624],[-76.2433,42.3664],[-76.2764,42.3794],[-76.2944,42.3816],[-76.2957,42.3866],[-76.2947,42.4075],[-76.2549,42.4082],[-76.1258,42.4107]]]},\"properties\":{\"name\":\"Tioga\",\"state\":\"NY\"}}]}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
Federal agencies that oversee land management for much of the Snake Range in eastern Nevada, including the management of Great Basin National Park by the National Park Service, need to understand the potential extent of adverse effects to federally managed lands from nearby groundwater development. As a result, this study was developed (1) to attain a better understanding of aquifers controlling groundwater flow on the eastern side of the southern part of the Snake Range and their connection with aquifers in the valleys, (2) to evaluate the relation between surface water and groundwater along the piedmont slopes, (3) to evaluate sources for Big Springs and Rowland Spring, and (4) to assess groundwater flow from southern Spring Valley into northern Hamlin Valley. The study focused on two areas—the first, a northern area along the east side of Great Basin National Park that included Baker, Lehman, and Snake Creeks, and a second southern area that is the potential source area for Big Springs. Data collected specifically for this study included the following: (1) geologic field mapping; (2) drilling, testing, and water quality sampling from 7 test wells; (3) measuring discharge and water chemistry of selected creeks and springs; (4) measuring streambed hydraulic gradients and seepage rates from 18 shallow piezometers installed into the creeks; and (5) monitoring stream temperature along selected reaches to identify places of groundwater inflow.
\nThe Snake Range was formed by a generally normal-faulted uplift, where late Proterozoic and Cambrian siliciclastic rocks and metamorphic rocks are present at the highest altitudes and younger Paleozoic carbonate rocks are exposed along the flanks. The consolidated rocks are intruded by Jurassic to Tertiary age plutons, which are most common between the Lehman and Snake Creek drainage basins. Older Cenozoic rocks, including Oligocene volcanic rocks and Miocene sedimentary rocks, crop out locally and fill the basins that underlie Snake, Spring, and Hamlin Valleys. Younger Tertiary and Quaternary sedimentary (basin-fill) deposits overlie the older Cenozoic rocks.
\nThe rocks and deposits can be divided into three distinct aquifers. These aquifers include (1) basin-fill aquifers that consist of the permeable parts of the Cenozoic basin fill and some fractured or jointed Cenozoic volcanic rocks, (2) an upper carbonate-rock aquifer that consists of upper Paleozoic carbonate rocks overlying a regionally extensive middle Paleozoic siliciclastic confining unit, and (3) a lower carbonate-rock aquifer that consists of lower Paleozoic carbonate rocks. Secondary openings created by faults, shear zones, fractures, and, in the carbonate rocks, karst solution features, largely determine the water-transmitting properties of the volcanic- and carbonate-rock aquifers. The basin-fill aquifers are composed of a wide variety of rock types and have highly variable hydraulic properties. The three aquifers are stratigraphically and structurally heterogeneous, causing large variations in the ability to store and transmit water. The aquifers are separated by confining units in some areas and are in contact with each other in other areas, yet function as a single, composite aquifer system. Basin-fill aquifers most often overlie or adjoin the lower and upper carbonate-rock aquifers.
\nBaker, Lehman and Snake Creek drainage basins were divided into five hydrologic zones on the basis of climate, geology, and topography. The five zones, from highest to lowest altitudes, are the mountain-upland, karst-limestone, upper-piedmont, lower-piedmont, and valley-lowland zones. The primary hydrologic connection between the mountain-upland and the valley-lowland zones is streamflow. Much of the streamflow from the mountain-upland zone is generated above tree line.
\nGroundwater flow increases in the karst-limestone zone because of increased permeability caused by dissolution, which results in increased streamflow losses. Most of the increased groundwater flow is to springs near faults that form the boundary with the upper-piedmont zone. Thus, groundwater flow from the karst-limestone zone to the upper-piedmont zone was only 10 percent of the combined flow of streams and springs that exit the karst-limestone zone. About 60 percent of the water flowing from Rowland Spring in the Lehman Creek drainage basin was from streamflow losses along Baker Creek. The remaining flow from Rowland Spring comes from local recharge in the karst-limestone zone.
\nIn the upper-piedmont zone, the water table by Baker, Lehman and Snake Creeks was near the water level in the creeks for several hundred feet downstream from the karst-limestone zone. Water levels in piezometers along Snake Creek downstream from its confluence with Spring Creek were far below the streambed, indicating gravity drainage beneath this section of the creek. Estimated vertical hydraulic conductivity along a 3-mile reach of Snake Creek downstream of this confluence was 0.5 foot per day, which was an order of magnitude less than that estimated for Baker and Lehman Creeks. The low vertical hydraulic conductivity in the streambed along the lower reaches of Snake Creek results from chemical precipitation of calcite caused by off-gassing of carbon dioxide derived from springs at the end of the karst-limestone zone.
\nThe younger alluvial deposits thicken rapidly across faults that form the upper boundary of the lower-piedmont zone. The absence of springs or groundwater flow to the creeks upstream of these faults indicates they are not a complete barrier to groundwater flow. The water table was shallow in the valley-lowland zone in the Baker and Lehman Creek drainage basins, whereas the water table was more than 50 feet below land surface in the Snake Creek drainage basin. In contrast to thick basin fill in the valley-lowland zone in the Baker and Lehman Creek drainage basins, fractured and karst limestone underlie basin fill at relatively shallow depths in Snake Creek drainage basin. The underlying limestone acts as a drain for groundwater in the basin fill beneath Snake Creek.
\nA groundwater divide in southern Spring Valley south of Baking Powder Flat separates groundwater flow to the flat from southeastward flow into northern Hamlin Valley. Groundwater flow from southern Spring Valley south of the groundwater divide into northern Hamlin Valley was estimated to range from 6,000 to 11,000 acre-feet per year. This groundwater does not flow to Big Springs in southern Snake Valley; rather, the source of water to Big Springs is groundwater recharge in the Big Spring Wash drainage basin and in nearby smaller drainage basins at the south end of the Snake Range.
\nGroundwater flow from southern Spring Valley continues through the western side of Hamlin Valley before being directed northeast toward the south end of Snake Valley. This flow is constrained by southward-flowing groundwater from Big Spring Wash and northward-flowing groundwater beneath central Hamlin Valley. The redirection to the northeast corresponds to a narrowing of the width of flow in southern Snake Valley caused by a constriction formed by a steeply dipping middle Paleozoic siliciclastic confining unit exposed in the flanks of the mountains and hills on the east side of southern Snake Valley and shallowly buried beneath basin fill in the valley. The narrowing of groundwater flow could be responsible for the large area where groundwater flows to springs or is lost to evapotranspiration between Big Springs in Nevada and Pruess Lake in Utah.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1819","collaboration":"Prepared in cooperation with the National Park Service, Bureau of Land Management, U.S. Fish and Wildlife Service, and U.S. Forest Service","usgsCitation":"Prudic, D.E, Sweetkind, D.S., Jackson, T.R., Dotson, K.E., Plume, R.W., Hatch, C.E., and Halford, K.J. 2015, Evaluating connection of aquifers to springs and streams, Great Basin National Park and vicinity, Nevada: U.S. Geological Survey Professional Paper 1819, 188 p., https://dx.doi.org/10.3133/pp1819.","productDescription":"Report: xxii, 187 p.; Appendixes 1-16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-034324","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":312322,"rank":16,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix14.zip","text":"Appendix 14","size":"4.3 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8"},{"id":312320,"rank":14,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix12.zip","text":"Appendix 12","size":"31 KB","linkFileType":{"id":6,"text":"zip"},"description":"PP 1819 Appendix 12"},{"id":312317,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix9.zip","text":"Appendix 9","size":"14 KB","linkFileType":{"id":6,"text":"zip"},"description":"PP 1819 Appendix 9"},{"id":312318,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix10.zip","text":"Appendix 10","size":"24 KB","linkFileType":{"id":6,"text":"zip"},"description":"PP 1819 Appendix 10"},{"id":312319,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix11.zip","text":"Appendix 11","size":"33 KB","linkFileType":{"id":6,"text":"zip"},"description":"PP 1819 Appendix 11"},{"id":312321,"rank":15,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix13.zip","text":"Appendix 13","size":"481 KB","linkFileType":{"id":6,"text":"zip"},"description":"PP 1819 Appendix 13"},{"id":312313,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix5.zip","text":"Appendix 5","size":"216 KB","linkFileType":{"id":6,"text":"zip"},"description":"PP 1819 Appendix 5"},{"id":312314,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1819/pp1819_appendix6.zip","text":"Appendix 6","size":"29 KB","linkFileType":{"id":6,"text":"zip"},"description":"PP 1819 Appendix 6"}],"country":"United States","state":"Nevada","county":"Lincoln County, White Pine County","otherGeospatial":"Baker Creek, Big Springs, Great Basin National Park, Hamlin Valley, Lehman Creek, Rowland Spring, Snake Range, Spring Valley, Snake 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Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
http://nevada.usgs.gov/water/
Benthic invertebrate communities are monitored because the composition of those communities can effect and be affected by the water quality of an aquatic system. Benthic communities use and sometimes regulate the cycling of essential elements (for example, carbon). Benthic invertebrate taxa may also indicate acutely and chronically stressful environments because they are mostly sessile, accumulate contaminants, and sometimes respond dramatically to oligotrophic as well as eutrophic conditions. Benthic communities can in turn affect water quality by grazing pelagic food resources and increasing the rate of nutrient regeneration through feeding and bioturbating the sediment.
South San Francisco Bay is a system dependent on phytoplankton as the base to the food web. Despite abundant nutrients, south San Francisco Bay has had limited phytoplankton production in the last several decades owning to poor light conditions and high grazing losses from the water column by benthic invertebrates. The south San Francisco Bay achieves a balance of biogeochemical conditions in most springs to accommodate a short phytoplankton bloom. This balance has maintained the phytoplankton in south San Francisco Bay at low biomass levels relative to other high-nutrient urban estuaries. The role that benthic invertebrates play in this balance, in these episodic spring events, and in other seasons within the estuary remains of great interest to water-quality and biological resource managers.
Our primary objective in this study is to quantify current (2014) benthic-community structure and function in the south San Francisco Bay sloughs and to compare those communities temporally over decadal time scales with a unique long-term dataset. The study area (fig. 1) is inclusive of the area south of the Dumbarton Bridge (DB) including Alviso and Guadalupe Sloughs and Coyote Creek.
The following are results highlighted in this report:
NRP staff, National Research Program
U.S. Geological Survey
345 Middlefield Road, MS-435
Menlo Park, CA 94025
http://water.usgs.gov/nrp/
A daily precipitation-runoff model was developed to estimate spatially and temporally distributed recharge for groundwater basins in the San Gorgonio Pass area, southern California. The recharge estimates are needed to define transient boundary conditions for a groundwater-flow model being developed to evaluate the effects of pumping and climate on the long-term availability of groundwater. The area defined for estimating recharge is referred to as the San Gorgonio Pass watershed model (SGPWM) and includes three watersheds: San Timoteo Creek, Potrero Creek, and San Gorgonio River. The SGPWM was developed by using the U.S. Geological Survey INFILtration version 3.0 (INFILv3) model code used in previous studies of recharge in the southern California region, including the San Gorgonio Pass area. The SGPWM uses a 150-meter gridded discretization of the area of interest in order to account for spatial variability in climate and watershed characteristics. The high degree of spatial variability in climate and watershed characteristics in the San Gorgonio Pass area is caused, in part, by the high relief and rugged topography of the area.
\nDaily climate data developed from a network of monitoring sites and published average monthly precipitation maps were used to develop the climate inputs for the SGPWM. Geographic Information System (GIS) data defining land surface altitude, vegetation, soils, surficial geology, and land cover were used to define input parameters representing the physical characteristics of the land surface, root zone, and shallow subsurface underlying the root zone. Model parameterization was based on a previous INFILv3 model developed for an area including the upper parts of the San Timoteo Creek and Potrero Creek drainages and the western part of the San Gorgonio River watershed. The previous INFILv3 model was calibrated by using available streamflow records from the model area. The SGPWM uses an updated INFILv3 version to represent shallow groundwater flow better beneath the root zone that contributes to lateral, downslope seepage rather than deep recharge. The SGPWM calibration was tested by using available streamflow records in the San Gorgonio Pass region.
\nThe SGPWM was used to simulate a 100-year water budget, including recharge and runoff, for water years 1913 through 2012. Results indicated that most recharge came from episodic infiltration of surface-water runoff in the larger stream channels. Results also indicated periods of great variability in recharge and runoff in response to variability in precipitation. More recharge was simulated for the area of the groundwater basin underlying the more permeable alluvial fill of the valley floor compared to recharge in the neighboring upland areas of the less permeable mountain blocks. The greater recharge was in response to the episodic streamflow that discharged from the mountain block areas and quickly infiltrated the permeable alluvial fill of the groundwater basin. Although precipitation at the higher altitudes of the mountain block was more than double precipitation at the lower altitudes of the valley floor, recharge for inter-channel areas of the mountain block was limited by the lower permeability bedrock underlying the thin soil cover, and most of the recharge in the mountain block was limited to the main stream channels underlain by alluvial fill.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155122","collaboration":"Prepared in cooperation with the San Gorgonio Pass Water Agency","usgsCitation":"Hevesi, J.A., and Christensen, A.H., 2015, Estimating natural recharge in San Gorgonio Pass watersheds, California, 1913–2012: U.S. Geological Survey Scientific Investigations Report 2015–5122, 74 p. https://dx.doi.org/10.3133/ SIR20155122.","productDescription":"xii, 74 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054946","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":312622,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5122/sir20155122.pdf","text":"Report","size":"29.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5122"},{"id":312621,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5122/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Gorgonio Pass","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.301025390625,\n 33.43831750748322\n ],\n [\n -116.05682373046875,\n 33.43831750748322\n ],\n [\n -116.05682373046875,\n 34.19135773925218\n ],\n [\n -117.301025390625,\n 34.19135773925218\n ],\n [\n -117.301025390625,\n 33.43831750748322\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
http://ca.water.usgs.gov
Bat mortality rates from white-nose syndrome and wind power development are unprecedented. Cryptic and wide-ranging behaviours of bats make them difficult to survey, and population estimation is often intractable. We advance a model-based framework for making spatially explicit predictions about summertime distributions of bats from capture and acoustic surveys. Motivated by species-energy and life-history theory, our models describe hypotheses about spatio-temporal variation in bat distributions along environmental gradients and life-history attributes, providing a statistical basis for conservation decision-making.
\nOregon and Washington, USA.
\nWe developed Bayesian hierarchical models for 14 bat species from an 8-year monitoring dataset across a ~430,000 km2 study area. Models accounted for imperfect detection and were temporally dynamic. We mapped predicted occurrence probabilities and prediction uncertainties as baselines for assessing future declines.
\nForest cover, snag abundance and cliffs were important predictors for most species. Species occurrence patterns varied along elevation and precipitation gradients, suggesting a potential hump-shaped diversity–productivity relationship. Annual turnover in occurrence was generally low, and occurrence probabilities were stable among most species. We found modest evidence that turnover covaried with the relative riskiness of bat roosting and migration. The fringed myotis (Myotis thysanodes), canyon bat (Parastrellus hesperus) and pallid bat (Antrozous pallidus) were rare; fringed myotis occurrence probabilities declined over the study period. We simulated anticipated declines to demonstrate that mapped occurrence probabilities, updated over time, provide an intuitive way to assess bat conservation status for a broad audience.
\nLandscape keystone structures associated with roosting habitat emerged as regionally important predictors of bat distributions. The challenges of bat monitoring have constrained previous species distribution modelling efforts to temporally static presence-only approaches. Our approach extends to broader spatial and temporal scales than has been possible in the past for bats, making a substantial increase in capacity for bat conservation.
","language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford","doi":"10.1111/ddi.12372","usgsCitation":"Rodhouse, T., Ormsbee, P., Irvine, K.M., Vierling, L.A., Szewczak, J.M., and Vierling, K.T., 2015, Establishing conservation baselines with dynamic distribution models for bat populations facing imminent decline: Diversity and Distributions, v. 21, no. 12, p. 1401-1413, https://doi.org/10.1111/ddi.12372.","startPage":"1401","endPage":"1413","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063534","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471560,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12372","text":"Publisher Index Page"},{"id":325981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","volume":"21","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-21","publicationStatus":"PW","scienceBaseUri":"57a1c42fe4b006cb45552c10","contributors":{"authors":[{"text":"Rodhouse, Thomas J.","contributorId":127378,"corporation":false,"usgs":false,"family":"Rodhouse","given":"Thomas J.","affiliations":[{"id":6924,"text":"National Park Service, Upper Columbia Basin Network","active":true,"usgs":false}],"preferred":false,"id":644350,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ormsbee, Patricia C.","contributorId":127379,"corporation":false,"usgs":false,"family":"Ormsbee","given":"Patricia C.","affiliations":[{"id":6925,"text":"US Forest Service, retired","active":true,"usgs":false}],"preferred":false,"id":644351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644349,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vierling, Lee A.","contributorId":169443,"corporation":false,"usgs":false,"family":"Vierling","given":"Lee","email":"","middleInitial":"A.","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":644352,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szewczak, Joseph M.","contributorId":30127,"corporation":false,"usgs":false,"family":"Szewczak","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":6958,"text":"Department of Biological Sciences, Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":644353,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vierling, Kerri T.","contributorId":140099,"corporation":false,"usgs":false,"family":"Vierling","given":"Kerri","email":"","middleInitial":"T.","affiliations":[{"id":13384,"text":"Department of Fish and Wildlife Sciences, University of Idaho,","active":true,"usgs":false}],"preferred":false,"id":644354,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70159986,"text":"ds975 - 2015 - The U.S. Geological Survey coal quality (COALQUAL) database version 3.0","interactions":[],"lastModifiedDate":"2015-12-21T14:50:46","indexId":"ds975","displayToPublicDate":"2015-12-21T15:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"975","title":"The U.S. Geological Survey coal quality (COALQUAL) database version 3.0","docAbstract":"Since the mid-1970s, the U.S. Geological Survey (USGS) has maintained a coal quality database of national scope named USCHEM, which currently contains data for over 13,000 samples. A subset of the USCHEM database called COALQUAL Version 1.3 was initially published in 1994 and was followed by Version 2.0 in 1997. Version 3.0 of the COALQUAL database represents a major editing effort to resolve some of the DOS software limitations used by earlier versions of the database.
\nBecause of database size limits during the development of COALQUAL Version 1.3, many analyses of individual bench samples were merged into whole coal bed averages. The methodology for making these composite intervals was not consistent. Size limits also restricted the amount of georeferencing information and forced removal of qualifier notations such as \"less than detection limit\" (<) information, which can cause problems when using the data. A review of the original data sheets revealed that COALQUAL Version 2.0 was missing information that was needed for a complete understanding of a coal section. Another important database issue to resolve was the USGS \"remnant moisture\" problem. Prior to 1998, tests for remnant moisture (as-determined moisture in the sample at the time of analysis) were not performed on any USGS major, minor, or trace element coal analyses. Without the remnant moisture, it is impossible to convert the analyses to a usable basis (as-received, dry, etc.). Based on remnant moisture analyses of hundreds of samples of different ranks (and known residual moisture) reported after 1998, it was possible to develop a method to provide reasonable estimates of remnant moisture for older data to make it more useful in COALQUAL Version 3.0. In addition, COALQUAL Version 3.0 is improved by (1) adding qualifiers, including statistical programming to deal with the qualifiers; (2) clarifying the sample compositing problems; and (3) adding associated samples. Version 3.0 of COALQUAL also represents the first attempt to incorporate data verification by mathematically crosschecking certain analytical parameters. Finally, a new database system was designed and implemented to replace the outdated DOS program used in earlier versions of the database.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds975","usgsCitation":"Palmer, C.A., Oman, C.L., Park, A.J., and Luppens, J.A., 2015, The U.S. Geological Survey coal quality (COALQUAL) database version 3.0: U.S. Geological Survey Data Series 975, 43 p. with appendixes, https://dx.doi.org/10.3133/ds975.","productDescription":"Report: v, 50 p.; Database","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-038492","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":312552,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0975/ds975.pdf","size":"5.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 975"},{"id":312553,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://ncrdspublic.er.usgs.gov/coalqual/","text":"COALQUAL Database","description":"DS 975"},{"id":312551,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0975/coverthb.jpg"}],"contact":"Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 913 National Center
12201 Sunrise Valley Drive
Reston, Virginia 20192
Or visit the USGS Eastern Energy Resources Science Center Web site at:
http://energy.usgs.gov/GeneralInfo/
ScienceCenters/Eastern.aspx
The Ozark aquifer, within the Ozark Plateaus aquifer system (herein referred to as the “Ozark system”), is the primary groundwater source in the Ozark Plateaus physiographic province (herein referred to as the “Ozark Plateaus”) of Arkansas, Kansas, Missouri, and Oklahoma. Groundwater from the Ozark system has historically been an important part of the water resource base, and groundwater availability is a concern in some areas; dependency on the Ozark aquifer as a water supply has caused evolving, localized issues. The construction of a regional potentiometric-surface map of the Ozark aquifer is needed to aid assessment of current and future groundwater use and availability. The regional potentiometric-surface mapping is part of the U.S. Geological Survey (USGS) Groundwater Resources Program initiative (http://water.usgs.gov/ogw/gwrp/activities/regional.html) and the Ozark system groundwater availability project (http://ar.water.usgs.gov/ozarks), which seeks to quantify current groundwater resources, evaluate changes in these resources over time, and provide the information needed to simulate system response to future human-related and environmental stresses.
The Ozark groundwater availability project objectives include assessing (1) growing demands for groundwater and associated declines in groundwater levels as agricultural, industrial, and public supply pumping increases to address needs; (2) regional climate variability and pumping effects on groundwater and surface-water flow paths; (3) effects of a gradual shift to a greater surface-water dependence in some areas; and (4) shale-gas production requiring groundwater and surface water for hydraulic fracturing. Data compiled and used to construct the regional Ozark aquifer potentiometric surface will aid in the assessment of those objectives.
Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, Arkansas 72211–3528
http://ar.water.usgs.gov/
The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, designed and operates a series of monitoring stations on streams and springs throughout Missouri known as the Ambient Water-Quality Monitoring Network. During the 2014 water year (October 1, 2013, through September 30, 2014), data were collected at 74 stations—72 Ambient Water-Quality Monitoring Network stations and 2 U.S. Geological Survey National Stream Quality Assessment Network stations. Dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, Escherichia coli bacteria, fecal coliform bacteria, dissolved nitrate plus nitrite as nitrogen, total phosphorus, dissolved and total recoverable lead and zinc, and select pesticide compound summaries are presented for 71 of these stations. The stations primarily have been classified into groups corresponding to the physiography of the State, primary land use, or unique station types. In addition, a summary of hydrologic conditions in the State including peak discharges, monthly mean discharges, and 7-day low flow is presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds971","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Barr, M.N., 2015, Quality of surface water in Missouri, water year 2014: U.S. Geological Survey Data Series 971, 22 p., https://dx.doi.org/10.3133/ds971.","productDescription":"vi, 22 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068828","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":312548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0971/coverthb.jpg"},{"id":312550,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0971/ds971.pdf","text":"Report","size":"2.05 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 971"}],"country":"United States","state":"Missouri","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.78979492187499,\n 40.60561205826018\n ],\n [\n -91.77978515625,\n 40.63896734381723\n ],\n [\n -91.56005859375,\n 40.48873742102282\n ],\n [\n -91.4501953125,\n 40.421860362045194\n ],\n [\n -91.51611328125,\n 40.17887331434696\n ],\n [\n -91.461181640625,\n 39.985538414809746\n ],\n [\n -91.417236328125,\n 39.842286020743394\n ],\n [\n -91.285400390625,\n 39.69873414348139\n ],\n [\n -91.01074218749999,\n 39.52099229357195\n ],\n [\n -90.692138671875,\n 39.198205348894795\n ],\n [\n -90.615234375,\n 39.01064750994083\n ],\n [\n -90.54931640625,\n 38.91668153637508\n ],\n [\n -90.439453125,\n 38.95940879245423\n ],\n [\n -90.1318359375,\n 38.89958342598271\n ],\n [\n -90.120849609375,\n 38.8225909761771\n ],\n [\n -90.15380859375,\n 38.659777730712534\n ],\n [\n -90.252685546875,\n 38.47939467327645\n ],\n [\n -90.340576171875,\n 38.315801006824984\n ],\n [\n -90.24169921875,\n 38.1777509666256\n ],\n [\n -90.010986328125,\n 38.048091067457236\n ],\n [\n -89.89013671875,\n 38.004819966413194\n ],\n [\n -89.659423828125,\n 37.84015683604136\n ],\n [\n -89.527587890625,\n 37.71859032558816\n ],\n [\n -89.45068359374999,\n 37.56199695314352\n ],\n [\n -89.45068359374999,\n 37.43125050179356\n ],\n [\n -89.5166015625,\n 37.29153547292737\n ],\n [\n -89.36279296875,\n 37.13404537126446\n ],\n [\n -89.307861328125,\n 37.00255267215955\n ],\n [\n -89.27490234375,\n 37.10776507118514\n ],\n [\n -89.154052734375,\n 37.020098201368114\n ],\n [\n -89.09912109375,\n 36.949891786813296\n ],\n [\n -89.1650390625,\n 36.81808022778526\n ],\n [\n -89.14306640625,\n 36.73888412439431\n ],\n [\n -89.154052734375,\n 36.67723060234619\n ],\n [\n -89.20898437499999,\n 36.58906837139909\n ],\n [\n -89.307861328125,\n 36.615527631349224\n ],\n [\n -89.384765625,\n 36.55377524336086\n ],\n [\n -89.483642578125,\n 36.46547188679816\n ],\n [\n -89.549560546875,\n 36.55377524336086\n ],\n [\n -89.549560546875,\n 36.474306755095206\n ],\n [\n -89.56054687499999,\n 36.31512514748051\n ],\n [\n -89.53857421875,\n 36.26199220445664\n ],\n [\n -89.67041015625,\n 36.2265501474709\n ],\n [\n -89.571533203125,\n 36.182224980422525\n ],\n [\n -89.69238281249999,\n 36.08462129606931\n ],\n [\n -89.703369140625,\n 36.02244668175846\n ],\n [\n -90.3955078125,\n 36.00467348670187\n ],\n [\n -90.32958984375,\n 36.11125252076159\n ],\n [\n -90.186767578125,\n 36.20882309283712\n ],\n [\n -90.087890625,\n 36.30627216957992\n ],\n [\n -90.06591796875,\n 36.37706783983682\n ],\n [\n -90.17578124999999,\n 36.41244153535644\n ],\n [\n -90.186767578125,\n 36.500805317604794\n ],\n [\n -94.625244140625,\n 36.50963615733049\n ],\n [\n -94.625244140625,\n 38.95940879245423\n ],\n [\n -94.68017578125,\n 39.155622393423215\n ],\n [\n -94.866943359375,\n 39.2407625100131\n ],\n [\n -94.888916015625,\n 39.308800296002914\n ],\n [\n -94.921875,\n 39.37677199661635\n ],\n [\n -95.0537109375,\n 39.49556336059472\n ],\n [\n -95.07568359375,\n 39.58029027440865\n ],\n [\n -95.020751953125,\n 39.707186656826565\n ],\n [\n -94.921875,\n 39.757879992021756\n ],\n [\n -94.89990234375,\n 39.825413103424786\n ],\n [\n -94.9658203125,\n 39.90130858574735\n ],\n [\n -95.042724609375,\n 39.884450178234395\n ],\n [\n -95.1416015625,\n 39.884450178234395\n ],\n [\n -95.29541015625,\n 39.9434364619742\n ],\n [\n -95.394287109375,\n 40.01920130768676\n ],\n [\n -95.43823242187499,\n 40.111688665595956\n ],\n [\n -95.482177734375,\n 40.195659093364654\n ],\n [\n -95.526123046875,\n 40.25437660372649\n ],\n [\n -95.657958984375,\n 40.29628651711716\n ],\n [\n -95.64697265625,\n 40.39676430557203\n ],\n [\n -95.723876953125,\n 40.538851525354644\n ],\n [\n -95.78979492187499,\n 40.60561205826018\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Missouri Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
http://mo.water.usgs.gov/
Since 2008, Rocky Mountain National Park in Colorado has been implementing an elk and vegetation management plan with the goal of managing elk populations and their habitats to improve the condition of key vegetation communities on elk winter range. Management actions that have been taken thus far include small reductions in the elk herd through culling of animals and temporary fencing of large areas of willow and aspen habitat to protect them from elk browsing. As part of the park’s elk and vegetation management plan (EVMP), a monitoring program was established to assess effectiveness of management actions in achieving vegetation goals. We collected data to monitor offtake (consumption) of upland herbaceous plants and willow annually from 2008 to 2014 and to assess aspen stand structure and regeneration and willow cover and height in 2013, 5 years after plan implementation. Loss of many willow and a few aspen monitoring sites to a fire in late 2012 complicated data collection and interpretation of results but will provide opportunities to observe habitat recovery following fire and in the presence and absence of elk herbivory, which will offer important insights into the use of prescribed fire as an additional management tool in these habitats.
\nIncreases in the number of small-diameter, tree-sized (stems greater than 2.5 meter height) aspen stems were observed but only inside fences that excluded ungulates. In unfenced areas, stand structure was stagnant, with many medium- and large-diameter (older) stems and no replacement of small-diameter stems. By 2013, aspen saplings (stems less than or equal to 2.5 meter height) were recruiting on 29 percent of sampled sites, an increase from 13 percent of sites at baseline, but this was mainly due to growth inside fences. Upland herbaceous offtake dropped below baseline levels (61 percent) on both core and noncore winter range in 2010–14. Less than 10 percent of the upland areas had intense herbivory (greater than 85 percent offtake), and less than 30 percent of the landscape had offtake greater than 70 percent after 2009. Offtake levels in 2013 and 2014 indicated an increase in grazing pressure on upland sites compared to 2010–12 levels, but this change may have been in response to loss of large patches of both herbaceous and woody forage in Moraine Park following the 2012 Fern Lake Fire. Winter willow offtake remained steady from 2009 to 2014, and although there were no substantial increases in offtake, there were also no consistent declines. Winter-range willow offtake was below the baseline level of 35 percent only in 2013 and 2014. Willow heights have stayed at or above baseline levels of 0.9 meter. Average heights of willow increased compared to baseline measures within fenced habitat on the core winter range and on noncore (all unfenced) winter range. Willow cover increased at least 75 percent compared to baseline within core winter-range fenced areas and roughly 25 percent in noncore winter range. Overall, during the first 5 years of implementation, the EVMP at Rocky Mountain National Park seems to be making steady progress toward the vegetation objectives set out by the EVMP. Habitat fencing has been the most effective means of improving aspen and willow habitat conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151216","collaboration":"In cooperation with the National Park Service","usgsCitation":"Zeigenfuss, L.C., and Johnson, T.L., 2015, Monitoring of vegetation response to elk population and habitat management in Rocky Mountain National Park, 2008–14: U.S. Geological Survey Open-File Report 2015–1216, 44 p., https://dx.doi.org/10.3133/ofr20151216.","productDescription":"vi, 44 p.","numberOfPages":"50","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057139","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":312403,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1216/ofr20151216.pdf","text":"Report","size":"8.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1216"},{"id":312401,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1216/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountain National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.83473205566406,\n 40.23183929314176\n ],\n [\n -105.57106018066406,\n 40.23183929314176\n ],\n [\n -105.57106018066406,\n 40.43440488077008\n ],\n [\n -105.83473205566406,\n 40.43440488077008\n ],\n [\n -105.83473205566406,\n 40.23183929314176\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526–8118
http://www.fort.usgs.gov/
Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
Continuous Slope-Area (CSA) gages were developed by the Arizona Water Science Center to enable the estimation of hydrographs when direct measurements of discharge cannot be made (Smith and others, 2010). CSA gages extend standard U.S. Geological Survey (USGS) methods for determining peak discharges to mid and high flows over a hydrograph computed at regular intervals with indirect measurement methods (Benson and Dalrymple, 1967; Dalrymple and Benson, 1967). CSA gages combine continuous stage records at two or more (typically three or four) cross sections with crosssection surveys and estimates of channel roughness to compute discharge over a range of flows. With standard indirect methods of determining peak discharge, water-surface elevation in the study reach at the peak flow is estimated from surveys of debris associated with the peak-flow water line. With CSA gages, stages are continuously measured at the cross sections, at regular and synchronized intervals (typically 5 minutes) over a flow event, and discharge can be calculated at each interval.
\nCalculation of discharge using indirect methods has been automated with the slope-area computation (SAC) program (Fulford, 1994). SAC is a widely used program within the USGS; it is easily run and displays output in a clear and convenient format, which includes flags that alert the user to shortcomings in the calculation. Use of SAC has been facilitated by SACGUI (Bradley, 2012; SACGUI uses a version of SAC called SAC7), a user interface that directly reads and displays survey data, allows for specification of water-surface slope and channel roughness, writes the input file for SAC7, runs SAC7, and displays SAC7 output.
\ncsa2sac is a program (appendix 1) that repeatedly runs SAC7 using stage data and a SAC7 input template file to compute the discharge at CSA gages. It is written in the C programming language, and is compatible with 64-bit Windows operating systems. The program reads a SAC7 input file and a file containing stage-data time series. It writes a new version of the SAC7 input file with the stage data for one time step, runs SAC7, then extracts computed discharges from the SAC7 output file and collates the discharges and stages to a separate file. It repeats these steps for each time interval in the stage file to produce a discharge time series from the stage data. csa2sac has been tested with two, three, four, and six cross sections and found to operate successfully. By running SAC7, csa2sac maintains consistency and comparability of both discharges calculated from CSA gages and of standard USGS methods for computing discharges indirectly. Brown and Metcalfe (2014) have made available alternative software for producing CSA discharges.
\nIn addition to csa2sac, the SAC7 program is required. It is the same as the original SAC program, except that it is compiled for 64-bit Windows operating systems and has a slightly different command line input. It is available online (http://water.usgs.gov/software/SAC/) as part of the SACGUI installation program. The program name, “SAC7.exe,” is coded into csa2sac, and must not be changed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151229","usgsCitation":"Wiele, S.M., 2015, csa2sac—A program for computing discharge from Continuous Slope-Area stage data: U.S. Geological Survey Open-File Report 2015–1229, 4 p., https://dx.doi.org/10.3133/ofr20151229.","productDescription":"Report: iii, 4 p.; Appendixes: 1-4; Companion File","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069076","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":311896,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1229/ofr20151229_appendix2_csa2sac.in","text":"Appendix 2 — csa2sac.in","size":"467 KB","description":"OFR 2015-1229 Appendix 2","linkHelpText":"Sample control file."},{"id":311895,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1229/ofr20151229_appendix1_csa2sac.cpp.txt","text":"Appendix 1 — csa2sac.cpp.txt","size":"6 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2015-1229 Appendix 1","linkHelpText":"csa2sac program code."},{"id":311897,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1229/ofr20151229_appendix3_sactemplate.txt","text":"Appendix 3 — sactemplate.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2015-1229 Appendix 3","linkHelpText":"Sample SAC input file used as template for csa2sac."},{"id":311898,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1229/ofr20151229_appendix4_stagedata.txt","text":"Appendix 4 — stagedata.txt","size":"20 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2015-1229 Appendix 4","linkHelpText":"Sample stage data input file."},{"id":311891,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1229/coverthb.jpg"},{"id":311892,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1229/ofr20151229.pdf","text":"Report","size":"191 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1229"},{"id":312279,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1229/ofr20151229_csa2sac_executable.zip","text":"Program — csa2sac.exe","size":"48 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2015-1229 Program csa2sac.exe","linkHelpText":"csa2sac program."}],"contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
http://az.water.usgs.gov/
The U.S. Geological Survey has a long history of responding to and documenting the impacts of storms along the Nation’s coasts and incorporating these data into storm impact and coastal change vulnerability assessments. These studies, however, have traditionally focused on sandy shorelines and sandy barrier-island systems, without consideration of impacts to coastal wetlands. The goal of the Barrier Island and Estuarine Wetland Physical Change Assessment project is to integrate a wetland-change assessment with existing coastal-change assessments for the adjacent sandy dunes and beaches, initially focusing on Assateague Island along the Maryland and Virginia coastline. Assateague Island was impacted by waves and storm surge associated with the passage of Hurricane Sandy in October 2012, including erosion and overwash along the ocean-facing sandy shoreline as well as erosion and overwash deposition in the back-barrier and estuarine bay environments.
\nThis report serves as an archive of data that were derived from Landsat 5 and Landsat 8 imagery from 1984 to 2014, including wetland and terrestrial habitat extents; open-ocean, back-barrier, and estuarine mainland shoreline positions; and sand-line positions along the estuarine mainland and barrier shorelines from Assateague Island, Maryland to Metompkin Island, Virginia. The geographic information system data files with accompanying formal Federal Geographic Data Committee metadata can be downloaded from the Data Downloads page.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds968","usgsCitation":"Bernier, J.C., Douglas, S.H., Terrano, J.F., Barras, J.A., Plant, N.G., and Smith, C.G., 2015, Land-cover types, shoreline positions, and sand extents derived from Landsat satellite imagery, Assateague Island to Metompkin Island, Maryland and Virginia, 1984 to 2014: U.S. Geological Survey Data Series 968, https://dx.doi.org/10.3133/ds968.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1984-01-01","temporalEnd":"2014-12-31","ipdsId":"IP-065873","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":312270,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0968/index.html","text":"Report (HTML format)","description":"DS 968"},{"id":312269,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0968/images/coverthb.jpg"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Assateague Island, Metompkin Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.10528564453125,\n 38.33303882235456\n ],\n [\n -75.25360107421875,\n 38.23925875585244\n ],\n [\n -75.5474853515625,\n 37.8065289741725\n ],\n [\n -75.30990600585938,\n 37.801103690609615\n ],\n [\n -75.02975463867188,\n 38.33088431959968\n ],\n [\n -75.10528564453125,\n 38.33303882235456\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
http://coastal.er.usgs.gov/
Wild waterfowl are primary reservoirs of avian influenza viruses (AIV). However the role of sea ducks in the ecology of avian influenza, and how that role differs from freshwater ducks, has not been examined. We obtained and analyzed sera from North Atlantic sea ducks and determined the seroprevalence in those populations. We also tested swab samples from North Atlantic sea ducks for the presence of AIV. We found relatively high serological prevalence (61%) in these sea duck populations but low virus prevalence (0.3%). Using these data we estimated that an antibody half-life of 141 weeks (3.2 years) would be required to attain these prevalences. These findings are much different than what is known in freshwater waterfowl and have implications for surveillance efforts, AIV in marine environments, and the roles of sea ducks and other long-lived waterfowl in avian influenza ecology.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0144524","usgsCitation":"Hall, J.S., Russell, R.E., Franson, J., Soos, C., Dusek, R.J., Allen, R.B., Nashold, S.W., Teslaa, J.L., Jonsson, J.E., Ballard, J.R., Harms, N.J., and Brown, J.D., 2015, Avian influenza ecology in North Atlantic sea ducks: Not all ducks are created equal: PLoS ONE, v. 10, no. 12, p. 1-16, https://doi.org/10.1371/journal.pone.0144524.","productDescription":"16 p.","startPage":"1","endPage":"16","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069941","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471563,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0144524","text":"Publisher Index Page"},{"id":316723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"12","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-17","publicationStatus":"PW","scienceBaseUri":"56bb1bbce4b08d617f654de1","contributors":{"authors":[{"text":"Hall, Jeffrey S. 0000-0001-5599-2826 jshall@usgs.gov","orcid":"https://orcid.org/0000-0001-5599-2826","contributorId":2254,"corporation":false,"usgs":true,"family":"Hall","given":"Jeffrey","email":"jshall@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":597668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Russell, Robin E. 0000-0001-8726-7303 rerussell@usgs.gov","orcid":"https://orcid.org/0000-0001-8726-7303","contributorId":3998,"corporation":false,"usgs":true,"family":"Russell","given":"Robin","email":"rerussell@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":597669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Franson, J. Christian jfranson@usgs.gov","contributorId":149318,"corporation":false,"usgs":true,"family":"Franson","given":"J. Christian","email":"jfranson@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":597670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Soos, Catherine","contributorId":99042,"corporation":false,"usgs":true,"family":"Soos","given":"Catherine","affiliations":[],"preferred":false,"id":597674,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":152316,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert","email":"rdusek@usgs.gov","middleInitial":"J.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":597671,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Allen, R. Bradford","contributorId":156366,"corporation":false,"usgs":false,"family":"Allen","given":"R.","email":"","middleInitial":"Bradford","affiliations":[{"id":20327,"text":"Maine Department of Inland Fisheries and Wildlife, Bangor, ME 04401","active":true,"usgs":false}],"preferred":false,"id":597675,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nashold, Sean W. 0000-0002-8869-6633 snashold@usgs.gov","orcid":"https://orcid.org/0000-0002-8869-6633","contributorId":3611,"corporation":false,"usgs":true,"family":"Nashold","given":"Sean","email":"snashold@usgs.gov","middleInitial":"W.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":597672,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Teslaa, Joshua L. 0000-0001-7802-3454 jteslaa@usgs.gov","orcid":"https://orcid.org/0000-0001-7802-3454","contributorId":5794,"corporation":false,"usgs":true,"family":"Teslaa","given":"Joshua","email":"jteslaa@usgs.gov","middleInitial":"L.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":597673,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jonsson, Jon Einar","contributorId":156367,"corporation":false,"usgs":false,"family":"Jonsson","given":"Jon","email":"","middleInitial":"Einar","affiliations":[{"id":20328,"text":"University of Iceland, Snæfellsnes Research Centre, Stykkishólmur, Iceland 245.","active":true,"usgs":false}],"preferred":false,"id":597676,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ballard, Jennifer R.","contributorId":127726,"corporation":false,"usgs":false,"family":"Ballard","given":"Jennifer","email":"","middleInitial":"R.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":597677,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Harms, Naomi Jnae","contributorId":156368,"corporation":false,"usgs":false,"family":"Harms","given":"Naomi","email":"","middleInitial":"Jnae","affiliations":[{"id":20329,"text":"Department of Veterinary Pathology, Western College of Veterinary Medicine,University of","active":true,"usgs":false}],"preferred":false,"id":597678,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Brown, Justin D.","contributorId":87838,"corporation":false,"usgs":false,"family":"Brown","given":"Justin","email":"","middleInitial":"D.","affiliations":[{"id":7125,"text":"Southeastern Cooperative Wildlife Disease Study, College of Veterinary Medicine, University of Georgia, Athens, GA 30602, USA.","active":true,"usgs":false}],"preferred":false,"id":597679,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70159489,"text":"ofr20151188B - 2015 - Standard operating procedures for collection of soil and sediment samples for the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy pilot study","interactions":[],"lastModifiedDate":"2016-08-26T09:43:25","indexId":"ofr20151188B","displayToPublicDate":"2015-12-17T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1188","chapter":"B","title":"Standard operating procedures for collection of soil and sediment samples for the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy pilot study","docAbstract":"An understanding of the effects on human and ecological health brought by major coastal storms or flooding events is typically limited because of a lack of regionally consistent baseline and trends data in locations proximal to potential contaminant sources and mitigation activities, sensitive ecosystems, and recreational facilities where exposures are probable. In an attempt to close this gap, the U.S. Geological Survey (USGS) has implemented the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy pilot study to collect regional sediment-quality data prior to and in response to future coastal storms. The standard operating procedure (SOP) detailed in this document serves as the sample-collection protocol for the SCoRR strategy by providing step-by-step instructions for site preparation, sample collection and processing, and shipping of soil and surficial sediment (for example, bed sediment, marsh sediment, or beach material). The objectives of the SCoRR strategy pilot study are (1) to create a baseline of soil-, sand-, marsh sediment-, and bed-sediment-quality data from sites located in the coastal counties from Maine to Virginia based on their potential risk of being contaminated in the event of a major coastal storm or flooding (defined as Resiliency mode); and (2) respond to major coastal storms and flooding by reoccupying select baseline sites and sampling within days of the event (defined as Response mode). For both modes, samples are collected in a consistent manner to minimize bias and maximize quality control by ensuring that all sampling personnel across the region collect, document, and process soil and sediment samples following the procedures outlined in this SOP. Samples are analyzed using four USGS-developed screening methods—inorganic geochemistry, organic geochemistry, pathogens, and biological assays—which are also outlined in this SOP. Because the SCoRR strategy employs a multi-metric approach for sample analyses, this protocol expands upon and reconciles differences in the sample collection protocols outlined in the USGS “National Field Manual for the Collection of Water-Quality Data,” which should be used in conjunction with this SOP. A new data entry and sample tracking system also is presented to ensure all relevant data and metadata are gathered at the sample locations and in the laboratories.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151188B","collaboration":"Toxic Substances Hydrology Program","usgsCitation":"Fisher, S.C., Reilly, T.J., Jones, D.K., Benzel, W.M., Griffin, D.W., Loftin, K.A., Iwanowicz, L.R., and Cohl, J.A., 2015, Standard operating procedure for collection of soil and sediment samples for the Sediment-bound Contaminant Resiliency and Response (SCoRR) strategy pilot study: U.S. Geological Survey Open-File Report 2015–1188b, 37 p., https://dx.doi.org/10.3133/ofr20151188B.","productDescription":"v, 37 p.","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066316","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":312385,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20151188A","text":"Open-File Report 2015-1188A","description":"OFR 2015-1188B","linkHelpText":"Strategy to Evaluate Persistent Contaminant Hazards Resulting from Sea-Level RiseToxic Substances Hydrology Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, Virginia 20192
http://www.usgs.gov/envirohealth/
http://health.usgs.gov/scorr/
Mudpuppy (Necturus maculosus maculosus) populations have been declining in the Great Lakes region of North America. However, during fisheries assessments in the Detroit River, we documented Mudpuppy reproduction when we collected all life stages from egg through adult as by-catch in fisheries assessments. Ten years of fisheries sampling resulted in two occurrences of Mudpuppy egg collection and 411 Mudpuppies ranging in size from 37–392 mm Total Length, collected from water 3.5–15.1 m deep. Different types of fisheries gear collected specific life stages; spawning females used cement structures for egg deposition, larval Mudpuppies found refuge in eggmats, and we caught adults with baited setlines and minnow traps. Based on logistic regression models for setlines and minnow traps, there was a higher probability of catching adult Mudpuppies at lower temperatures and in shallower water with reduced clarity. In addition to documenting the presence of all life stages of this sensitive species in a deep and fast-flowing connecting channel, we were also able to show that standard fisheries research equipment can be used for Mudpuppy research in areas not typically sampled in herpetological studies. Our observations show that typical fisheries assessments and gear can play an important role in data collection for Mudpuppy population and spawning assessments.
","language":"English","publisher":"Partners in Amphibian and Reptile Conservation","publisherLocation":"Texarkana, TX","usgsCitation":"Craig, J.M., Mifsud, D.A., Briggs, A., Boase, J., and Kennedy, G.W., 2015, Mudpuppy (Necturus maculosus maculosus ) spatial distribution, breeding water depth, and use of artificial spawning habitat in the Detroit River: Herpetological Conservation and Biology, v. 10, no. 3, p. 926-934.","productDescription":"9 p.","startPage":"926","endPage":"934","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059198","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":313969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":313967,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.herpconbio.org/Volume_10/Issue_3/Craig_etal_2015.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"Canada, United States","state":"Michigan, Ontario","otherGeospatial":"Detroit River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.91107177734375,\n 42.37985076434416\n ],\n [\n -82.90145874023438,\n 42.33215399891373\n ],\n [\n -82.97286987304688,\n 42.32606244456202\n ],\n [\n -83.0511474609375,\n 42.30879983710441\n ],\n [\n -83.09234619140625,\n 42.272228095985675\n ],\n [\n -83.09371948242188,\n 42.21122801157102\n ],\n [\n -83.09371948242188,\n 42.14507804381756\n ],\n [\n -83.08273315429688,\n 42.042153895364\n ],\n [\n -83.21456909179688,\n 42.03501434990212\n ],\n [\n -83.19808959960936,\n 42.13082130188811\n ],\n [\n -83.15826416015625,\n 42.207159242513335\n ],\n [\n -83.1610107421875,\n 42.24173542549948\n ],\n [\n -83.1390380859375,\n 42.26917949243506\n ],\n [\n -83.09097290039062,\n 42.31997030030751\n ],\n [\n -83.02780151367188,\n 42.355499492256534\n ],\n [\n -82.99621582031249,\n 42.36869093640926\n ],\n [\n -82.91107177734375,\n 42.37985076434416\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"568e491de4b0e7a44bc41a0a","contributors":{"authors":[{"text":"Craig, Jaquelyn M. 0000-0002-7601-8616 jcraig@usgs.gov","orcid":"https://orcid.org/0000-0002-7601-8616","contributorId":146209,"corporation":false,"usgs":true,"family":"Craig","given":"Jaquelyn","email":"jcraig@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":566610,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mifsud, David A.","contributorId":146210,"corporation":false,"usgs":false,"family":"Mifsud","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":16628,"text":"Herpetological Resource and Management, LLC","active":true,"usgs":false}],"preferred":false,"id":566611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Andrew S.","contributorId":32796,"corporation":false,"usgs":true,"family":"Briggs","given":"Andrew S.","affiliations":[],"preferred":false,"id":566612,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boase, James C.","contributorId":38077,"corporation":false,"usgs":false,"family":"Boase","given":"James C.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":566613,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kennedy, Gregory W. 0000-0003-1686-6960 gkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-1686-6960","contributorId":3700,"corporation":false,"usgs":true,"family":"Kennedy","given":"Gregory","email":"gkennedy@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":566614,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70160029,"text":"ofr20151232 - 2015 - California State Waters map series — Offshore of Pigeon Point, California","interactions":[],"lastModifiedDate":"2022-04-18T21:45:34.762725","indexId":"ofr20151232","displayToPublicDate":"2015-12-15T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1232","title":"California State Waters map series — Offshore of Pigeon Point, California","docAbstract":"In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
\nThe Offshore of Pigeon Point map area is located in central California, on the Pacific Coast about 50 km south of San Francisco and 25 km northwest of Santa Cruz. The onshore part of the map area is sparsely populated. The nearest significant onshore cultural center is Pescadero, an unincorporated community with a population of well under 1,000. The hilly coastal area is virtually undeveloped, used primarily for agricultural or as grazing land for sheep and cattle. Agriculture is limited to the coastal uplifted Pleistocene marine terraces and upper Pleistocene alluvial fan deposits, which lie between the shoreline and the northwest-trending Santa Cruz Mountains.
\nThe map area is cut by the San Gregorio Fault Zone, and is located a few kilometers southwest of the San Andreas Fault Zone. Coastal uplift and folding in the map area has been attributed to a westward bend in the San Andreas Fault Zone and also to right-lateral movement along the San Gregorio Fault Zone. The irregular coastal geomorphology of this area, which consists of low, rocky cliffs and sparse, small pocket beaches backed by low, terraced hills, is partly attributable to this ongoing deformation.
\nThe shelf in the map area is underlain by variable amounts (0 to 20 m) of upper Quaternary nearshore and shelf sediments deposited as sea level fluctuated in the late Pleistocene. The southern part of the map is characterized by the presence of uplifted bedrock that has been linked to a local zone of transpression in the San Gregorio Fault Zone. This uplift, coupled with high wave energy, has resulted in little or no sediment cover in this area where exposures of bedrock are present at water depths of as much as 45 m. The thickest deposits of sediment are located in the northern part of the map area.
\nCoastal sediment transport in the map area is characterized by north-to-south littoral transport of sediment that is derived mainly from streams in the Santa Cruz Mountains and also from local coastal erosion. Shoreline-change studies indicate long-term erosion; within the region between San Francisco and Davenport, the highest long- and short-term coastal-erosion rates occur in the map area, just north of Point Año Nuevo. During the last approximately 300 years, as much as 18 million cubic yards (14 million cubic meters) of sand-sized sediment has been eroded from the area between Año Nuevo Island and Point Año Nuevo and transported south. Once widened by this pulse of eroded sediment, beaches south of Point Año Nuevo are now narrowing as the tail end of this mass of sand progresses farther south.
\nThe Offshore of Pigeon Point map area lies within the cold-temperate biogeographic zone that is called either the “Oregonian province” or the “northern California ecoregion.” This biogeographic province is maintained by the long-term stability of the southward-flowing California Current, the eastern limb of the North Pacific subtropical gyre that flows from southern British Columbia to Baja California. At its midpoint off central California, the California Current transports subarctic surface (0–500 m deep) waters southward, about 150 to 1,300 km from shore. Seasonal northwesterly winds that are, in part, responsible for the California Current, generate coastal upwelling. The south end of the Oregonian province is at Point Conception (about 335 km south of the map area), although its associated phylogeographic group of marine fauna may extend beyond to the area offshore of Los Angeles in southern California. The ocean off of central California has experienced a warming over the last 50 years that is driving an ecosystem shift away from the productive subarctic regime towards a depopulated subtropical environment.
\nSeafloor habitats in the Offshore of Pigeon Point map area lie within the Shelf (continental shelf) megahabitat. Significant rocky outcrops, which support kelp-forest communities in the nearshore and rocky-reef communities in deeper water, dominate the inner shelf waters. Biological productivity resulting from coastal upwelling supports populations of Sooty Shearwater, Western Gull, Common Murre, Cassin’s Auklet, and many other less populous bird species. In addition, an observable recovery of Humpback and Blue Whales has occurred in the area; both species are dependent on coastal upwelling to provide nutrients. The large extent of exposed inner shelf bedrock supports large forests of “bull kelp,” which is well adapted for high-wave-energy environments. Common fish species found in the kelp beds and rocky reefs include lingcod and various species of rockfish and greenling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151232","usgsCitation":"Cochrane, G.R., Watt, J.T., Dartnell, P., Greene, H.G., Erdey, M.D., Dieter, B.E., Golden, N.E., Johnson, S.Y., Endris, C.A., Hartwell, S.R., Kvitek, R.G., Davenport, C.W., Krigsman, L.M., Ritchie, A.C., Sliter, R.W., Finlayson, D.P., and Maier, K.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Pigeon Point, California: U.S. Geological Survey Open-File Report 2015–1232, pamphlet 40 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151232.","productDescription":"Pamphlet: iv, 40 p.; 10 Sheets: 50.50 x 36.00 inches or smaller; Data Catalog; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057881","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438659,"rank":21,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7513W80","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Offshore of Pigeon Point, California"},{"id":312124,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20151191","text":"Open-File Report 2015-1191","linkHelpText":"California State Waters Map Series—Offshore of Scott Creek, California, by Guy R. Cochrane and others."},{"id":399012,"rank":20,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_103761.htm"},{"id":312123,"rank":14,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/781/","text":"Data Series 781","linkHelpText":"California State Waters Map Series Data Catalog"},{"id":312122,"rank":13,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_metadata.html","linkFileType":{"id":5,"text":"html"}},{"id":312121,"rank":12,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7513W80","text":"Data Catalog","linkFileType":{"id":5,"text":"html"},"linkHelpText":"The GIS data layers for this map are accessible from “Data Catalog—Offshore Pigeon Point, California,” which is part of California State Waters Map Series Data Catalog. Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."},{"id":312119,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet9.pdf","text":"Sheet 9","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 9 PDF","linkHelpText":"Local (Offshore of Pigeon Point Map Area) and Regional (Offshore from Pigeon Point to Southern Monterey Bay) Shallow-Subsurface Geology and Structure, California By Janet T. Watt, Samuel Y. Johnson, Stephen R. Hartwell, Ray W. Sliter, and Katherine L. Maier"},{"id":312128,"rank":19,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1232/coverthb.jpg"},{"id":312127,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2014/1260/","text":"Open-File Report 2014–1260","linkHelpText":"California State Waters Map Series—Offshore of Pacifica, California, by Brian D. 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Erdey"},{"id":312111,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 1 PDF","linkHelpText":"Colored Shaded-Relief Bathymetry, Offshore of Pigeon Point Map Area, California By Peter Dartnell, Rikk G. Kvitek, Andrew C. Ritchie, and David P. Finlayson"},{"id":312112,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 2 PDF","linkHelpText":"Shaded-Relief Bathymetry, Offshore of Pigeon Point Map Area, California By Peter Dartnell, Rikk G. Kvitek, Andrew C. Ritchie, and David P. Finlayson"},{"id":312113,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 3 PDF","linkHelpText":"Acoustic Backscatter, Offshore of Pigeon Point Map Area, California By Peter Dartnell, Rikk G. Kvitek, Andrew C. Ritchie, and David P. Finlayson"},{"id":312114,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet4.pdf","text":"Sheet 4","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 4 PDF","linkHelpText":"Data Integration and Visualization, Offshore of Pigeon Point Map Area, California By Peter Dartnell"},{"id":312110,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Pamphlet PDF"},{"id":312115,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet5.pdf","text":"Sheet 5","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 5 PDF","linkHelpText":"Seafloor Character, Offshore of Pigeon Point Map Area, California By Mercedes D. Erdey and Guy R. Cochrane"},{"id":312116,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1232/ofr20151232_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1232 Sheet 6 PDF","linkHelpText":"Ground-Truth Studies, Offshore of Pigeon Point Map Area, California By Nadine E. Golden, Guy R. Cochrane, and Lisa M. Krigsman"}],"scale":"24000","country":"United States","state":"California","otherGeospatial":"Pigeon Point","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.4853,\n 37.0756\n ],\n [\n -122.4853,\n 37.2347\n ],\n [\n -122.2858,\n 37.2347\n ],\n [\n -122.2858,\n 37.0756\n ],\n [\n -122.4853,\n 37.0756\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2015-12-15","noUsgsAuthors":false,"publicationDate":"2015-12-15","publicationStatus":"PW","scienceBaseUri":"567139aee4b09cfe53ca7d58","contributors":{"editors":[{"text":"Cochrane, Guy R. 0000-0002-8094-4583 gcochrane@usgs.gov","orcid":"https://orcid.org/0000-0002-8094-4583","contributorId":2870,"corporation":false,"usgs":true,"family":"Cochrane","given":"Guy","email":"gcochrane@usgs.gov","middleInitial":"R.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":581771,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cochran, Susan A. 0000-0002-2442-8787 scochran@usgs.gov","orcid":"https://orcid.org/0000-0002-2442-8787","contributorId":2062,"corporation":false,"usgs":true,"family":"Cochran","given":"Susan A.","email":"scochran@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":581772,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Cochrane, Guy R. 0000-0002-8094-4583 gcochrane@usgs.gov","orcid":"https://orcid.org/0000-0002-8094-4583","contributorId":2870,"corporation":false,"usgs":true,"family":"Cochrane","given":"Guy","email":"gcochrane@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":581625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watt, Janet 0000-0002-4759-3814 jwatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":146222,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","email":"jwatt@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":581626,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dartnell, Peter 0000-0002-9554-729X pdartnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9554-729X","contributorId":2688,"corporation":false,"usgs":true,"family":"Dartnell","given":"Peter","email":"pdartnell@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":581627,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Greene, H. 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2015 - Sediment transport and evaluation of sediment surrogate ratings in the Kootenai River near Bonners Ferry, Idaho, Water Years 2011–14","interactions":[],"lastModifiedDate":"2015-12-14T15:02:54","indexId":"sir20155169","displayToPublicDate":"2015-12-14T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5169","title":"Sediment transport and evaluation of sediment surrogate ratings in the Kootenai River near Bonners Ferry, Idaho, Water Years 2011–14","docAbstract":"
The Kootenai River white sturgeon (Acipenser transmontanus) and other native fish species are culturally important to the Kootenai Tribe of Idaho, but their habitat and recruitment have been affected by anthropogenic changes to the river. Although the interconnections among anthropogenic changes and their impacts on fish are complex, the Kootenai Tribe of Idaho, in cooperation with other agencies, has been trying to understand and promote native fish recruitment through the development and implementation of the Kootenai River Habitat Restoration Program. As part of this effort, the U.S. Geological Survey collected sediment and streamflow information and evaluated use of acoustic backscatter as a sediment surrogate for estimating continuous suspended-sediment concentration at three sites in the Kootenai River white sturgeon critical habitat during water years 2011–14.
\nDuring the study, total suspended-sediment and fines concentrations were driven primarily by contributions from tributaries flowing into the Kootenai River between Libby Dam and the study area and were highest during rain-on-snow events in those tributary watersheds. On average, the relative percentage of suspended-sediment concentration in equal-width-increment samples collected in water years 2011–14 composed of fines less than 0.0625 mm (called washload) was 73, 71, and 70 percent at the Below Moyie, Crossport, and Tribal Hatchery sites, respectively. Suspended sand transport often increased with high streamflows, typically but not always associated with releases from Libby Dam. Bedload measured at the Crossport site was about 5 percent, on average, of the total sediment load measured in samples collected in water years 2011–13 and was positively correlated with suspended-sediment load. Comparisons with regional regression and envelope lines for suspended-sediment and bedload transport in relation to unregulated drainage area (drainage area downstream of Libby Dam) show that sediment transport was substantially less in the Kootenai River than in selected, minimally regulated Rocky Mountain rivers.
\nAcoustic surrogate ratings were developed between backscatter data collected using acoustic Doppler velocity meters (ADVMs) and results of suspended-sediment samples. Ratings were successfully fit to various sediment size classes (total, fines, and sands) using ADVMs of different frequencies (1.5 and 3 megahertz). Surrogate ratings also were developed using variations of streamflow and seasonal explanatory variables. The streamflow surrogate ratings produced average annual sediment load estimates that were 8–32 percent higher, depending on site and sediment type, than estimates produced using the acoustic surrogate ratings. The streamflow surrogate ratings tended to overestimate suspended-sediment concentrations and loads during periods of elevated releases from Libby Dam as well as on the falling limb of the streamflow hydrograph. Estimates from the acoustic surrogate ratings more closely matched suspended-sediment sample results than did estimates from the streamflow surrogate ratings during these periods as well as for rating validation samples collected in water year 2014. Acoustic surrogate technologies are an effective means to obtain continuous, accurate estimates of suspended-sediment concentrations and loads for general monitoring and sediment-transport modeling. In the Kootenai River, continued operation of the acoustic surrogate sites and use of the acoustic surrogate ratings to calculate continuous suspended-sediment concentrations and loads will allow for tracking changes in sediment transport over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155169","collaboration":"Prepared in cooperation with the Kootenai Tribe of Idaho","usgsCitation":"Wood, M.S., Fosness, R.L., and Etheridge, A.B., 2015, Sediment transport and evaluation of sediment surrogate ratings in the Kootenai River near Bonners Ferry, Idaho, water years 2011–14: U.S. Geological Survey Scientific Investigations Report 2015–5169, 48 p., https://dx.doi.org/10.3133/sir20155169.","productDescription":"Report:vi, 45 p.; Appendix","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-046285","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":312256,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5169/sir20155169.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5169 Report PDF"},{"id":312257,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5169/sir20155169_appendixA.xlsx","text":"Appendix A","size":"87 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5169 Appendix A"},{"id":312255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5169/coverthb.jpg"}],"country":"United States","state":"Idaho","city":"Bonners Ferry","otherGeospatial":"Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.57318115234375,\n 48.65014969395597\n ],\n [\n -116.57318115234375,\n 48.94505319583951\n ],\n [\n -116.04858398437499,\n 48.94505319583951\n ],\n [\n -116.04858398437499,\n 48.65014969395597\n ],\n [\n -116.57318115234375,\n 48.65014969395597\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
The economic vitality and national security of the United States depend on the reliable supply of numerous nonfuel mineral commodities. Over the past six decades, many of these commodities have been sourced increasingly from outside the United States. The mix of commodities for which the United States is import dependent has changed as technologies have advanced, as substitute materials have been developed, and as world economies have changed. Although reliance on imports is only one of the many factors that determine supply risk, a clear, long-term trend has emerged from the data compiled and published by the U.S. Geological Survey, National Minerals Information Center (USGS–NMIC), and its predecessor organizations. Because the global distribution of mineral resources and reserves is not uniform, the United States has always been import reliant for some mineral commodities. Essentially, the type of commodities and the countries from which they are sourced determine risk related to import dependence. In light of projections that 2.5 billion to 3 billion people globally could move into the middle class by 2030, the demand for many types of mineral commodities is likely to continue to increase. Recent concerns regarding so-called “critical minerals” have been driven by market dislocations in the rare-earth-element supply chain in 2010 that resulted from a short-term policy decision by the Government of the People’s Republic of China to limit exports. That policy has since been changed as a result of actions by the World Trade Organization, but the events that followed, such as higher prices and intensive efforts to diversify sources of supply, illustrate the underlying issues of supply risk and the influence that disruptions can have on supply. These factors are often used in the classification of a mineral commodity as “critical.”
\nThe USGS–NMIC collects, analyzes, and disseminates information on a monthly, quarterly, or annual basis for more than 90 nonfuel mineral commodities from more than 180 countries. These data indicate that from 1954 through 2014 there was (1) a clear increase in the number and type of nonfuel mineral commodities for which the United States was net import reliant, (2) an increase in the percentage of import reliance for individual nonfuel mineral commodities, and (3) a shift in the geographic distribution of the source countries.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153082","usgsCitation":"Fortier, S.M., DeYoung, J.H., Jr., Sangine, E.S., and Schnebele, E.K., 2015, Comparison of U.S. net import reliance for nonfuel mineral commodities—A 60-year retrospective (1954–1984–2014): U.S. Geological Survey Fact Sheet 2015–3082, 4 p., https://dx.doi.org/10.3133/fs20153082.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069937","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":312149,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3082/coverthb.jpg"},{"id":312150,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3082/fs20153082.pdf","text":"Report","size":"2.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3082"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Or visit the USGS Minerals Information Web site at http://minerals.usgs.gov/minerals/
","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2015-12-14","noUsgsAuthors":false,"publicationDate":"2015-12-14","publicationStatus":"PW","scienceBaseUri":"566fe82ae4b09cfe53ca7951","contributors":{"authors":[{"text":"Fortier, Steven M. sfortier@usgs.gov","contributorId":140391,"corporation":false,"usgs":true,"family":"Fortier","given":"Steven M.","email":"sfortier@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":580636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeYoung, Jr. 0000-0003-1169-6026 jdeyoung@usgs.gov","orcid":"https://orcid.org/0000-0003-1169-6026","contributorId":523,"corporation":false,"usgs":true,"family":"DeYoung","suffix":"Jr.","email":"jdeyoung@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":580637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sangine, Elizabeth S. escottsangine@usgs.gov","contributorId":5806,"corporation":false,"usgs":true,"family":"Sangine","given":"Elizabeth","email":"escottsangine@usgs.gov","middleInitial":"S.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":580638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schnebele, Emily K. eschnebele@usgs.gov","contributorId":139796,"corporation":false,"usgs":true,"family":"Schnebele","given":"Emily","email":"eschnebele@usgs.gov","middleInitial":"K.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":580639,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70164517,"text":"70164517 - 2015 - Mapping geoelectric fields during magnetic storms: Synthetic analysis of empirical United States impedances","interactions":[],"lastModifiedDate":"2016-02-09T13:05:23","indexId":"70164517","displayToPublicDate":"2015-12-14T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Mapping geoelectric fields during magnetic storms: Synthetic analysis of empirical United States impedances","docAbstract":"Empirical impedance tensors obtained from EarthScope magnetotelluric data at sites distributed across the midwestern United States are used to examine the feasibility of mapping magnetic storm induction of geoelectric fields. With these tensors, in order to isolate the effects of Earth conductivity structure, we perform a synthetic analysis—calculating geoelectric field variations induced by a geomagnetic field that is geographically uniform but varying sinusoidally with a chosen set of oscillation frequencies that are characteristic of magnetic storm variations. For north-south oriented geomagnetic oscillations at a period of T0=100 s, induced geoelectric field vectors show substantial geographically distributed differences in amplitude (approximately a factor of 100), direction (up to 130∘), and phase (over a quarter wavelength). These differences are the result of three-dimensional Earth conductivity structure, and they highlight a shortcoming of one-dimensional conductivity models (and other synthetic models not derived from direct geophysical measurement) that are used in the evaluation of storm time geoelectric hazards for the electric power grid industry. A hypothetical extremely intense magnetic storm having 500 nT amplitude at T0=100 s would induce geoelectric fields with an average amplitude across the midwestern United States of about 2.71 V/km, but with a representative site-to-site range of 0.15 V/km to 16.77 V/km. Significant improvement in the evaluation of such hazards will require detailed knowledge of the Earth's interior three-dimensional conductivity structure.
\n","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015GL066636","usgsCitation":"Bedrosian, P.A., and Love, J.J., 2015, Mapping geoelectric fields during magnetic storms: Synthetic analysis of empirical United States impedances: Geophysical Research Letters, v. 42, no. 23, p. 10160-10170, https://doi.org/10.1002/2015GL066636.","productDescription":"11 p.","startPage":"10160","endPage":"10170","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070730","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471565,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl066636","text":"Publisher Index Page"},{"id":316741,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"23","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-14","publicationStatus":"PW","scienceBaseUri":"56bb1bc7e4b08d617f654e29","contributors":{"authors":[{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":597711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":597712,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70161863,"text":"70161863 - 2015 - The role of dynamic surface water-groundwater exchange on streambed denitrification in a first-order, low-relief agricultural watershed","interactions":[],"lastModifiedDate":"2016-12-16T10:44:50","indexId":"70161863","displayToPublicDate":"2015-12-13T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"The role of dynamic surface water-groundwater exchange on streambed denitrification in a first-order, low-relief agricultural watershed","docAbstract":"
The role of temporally varying surface water-groundwater (SW-GW) exchange on nitrate removal by streambed denitrification was examined along a reach of Leary Weber Ditch (LWD), Indiana, a small, first-order, low-relief agricultural watershed within the Upper Mississippi River basin, using data collected in 2004 and 2005. Stream stage, GW heads (H), and temperatures (T) were continuously monitored in streambed piezometers and stream bank wells for two transects across LWD accompanied by synoptic measurements of stream stage, H, T, and nitrate (NO3) concentrations along the reach. The H and T data were used to develop and calibrate vertical two-dimensional, models of streambed water flow and heat transport across and along the axis of the stream. Model-estimated SW-GW exchange varied seasonally and in response to high-streamflow events due to dynamic interactions between SW stage and GW H. Comparison of 2004 and 2005 conditions showed that small changes in precipitation amount and intensity, evapotranspiration, and/or nearby GW levels within a low-relief watershed can readily impact SW-GW interactions. The calibrated LWD flow models and observed stream and streambed NO3 concentrations were used to predict temporal variations in streambed NO3 removal in response to dynamic SW-GW exchange. NO3 removal rates underwent slow seasonal changes, but also underwent rapid changes in response to high-flow events. These findings suggest that increased temporal variability of SW-GW exchange in low-order, low-relief watersheds may be a factor contributing their more efficient removal of NO3.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014WR016739","usgsCitation":"Rahimi Kazerooni, M.N., Essaid, H.I., and Wilson, J.T., 2015, The role of dynamic surface water-groundwater exchange on streambed denitrification in a first-order, low-relief agricultural watershed: Water Resources Research, v. 51, no. 12, p. 9514-9538, https://doi.org/10.1002/2014WR016739.","productDescription":"25 p.","startPage":"9514","endPage":"9538","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061362","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471568,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014wr016739","text":"Publisher Index Page"},{"id":314041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Indiana","otherGeospatial":"Leary Weber Ditch","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.83828449249268,\n 39.854443814802465\n ],\n [\n -85.84047317504883,\n 39.85763940869116\n ],\n [\n -85.84309101104736,\n 39.85974776029954\n ],\n [\n -85.84562301635741,\n 39.86034072251865\n ],\n [\n -85.84811210632324,\n 39.85987953012439\n ],\n [\n -85.84965705871582,\n 39.85796884289973\n ],\n [\n -85.84982872009277,\n 39.85609104672825\n ],\n [\n -85.84794044494629,\n 39.85605810247719\n ],\n [\n -85.84725379943846,\n 39.85757352165968\n ],\n [\n -85.8457088470459,\n 39.85819944590483\n ],\n [\n -85.84377765655518,\n 39.85721114185585\n ],\n [\n -85.83987236022949,\n 39.853323674511145\n ],\n [\n -85.83871364593504,\n 39.85137985826863\n ],\n [\n -85.83768367767334,\n 39.84798628442432\n ],\n [\n -85.83673954010008,\n 39.846108215141285\n ],\n [\n -85.8330488204956,\n 39.84561397784372\n ],\n [\n -85.8301305770874,\n 39.84479024110811\n ],\n [\n -85.82794189453125,\n 39.841989462283536\n ],\n [\n -85.82360744476318,\n 39.84192356022963\n ],\n [\n -85.82369327545166,\n 39.84334044044997\n ],\n [\n -85.82661151885986,\n 39.843406341144004\n ],\n [\n -85.82824230194092,\n 39.84558102856405\n ],\n [\n -85.82961559295654,\n 39.8466353976705\n ],\n [\n -85.83193302154541,\n 39.847294370139366\n ],\n [\n -85.8345079421997,\n 39.84782154356041\n ],\n [\n -85.83566665649414,\n 39.84834871293334\n ],\n [\n -85.83600997924805,\n 39.85049029688317\n ],\n [\n -85.83828449249268,\n 39.854443814802465\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-13","publicationStatus":"PW","scienceBaseUri":"5690ebd1e4b09c7f9a218bec","contributors":{"authors":[{"text":"Rahimi Kazerooni, Mina N. mrahimikazerooni@usgs.gov","contributorId":5706,"corporation":false,"usgs":true,"family":"Rahimi Kazerooni","given":"Mina","email":"mrahimikazerooni@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":587984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Essaid, Hedeff I. 0000-0003-0154-8628 hiessaid@usgs.gov","orcid":"https://orcid.org/0000-0003-0154-8628","contributorId":2284,"corporation":false,"usgs":true,"family":"Essaid","given":"Hedeff","email":"hiessaid@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":587983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, John T. 0000-0001-6752-4069 jtwilson@usgs.gov","orcid":"https://orcid.org/0000-0001-6752-4069","contributorId":1954,"corporation":false,"usgs":true,"family":"Wilson","given":"John","email":"jtwilson@usgs.gov","middleInitial":"T.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":587985,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159654,"text":"fs20153079 - 2015 - Shift in Global Tantalum Mine Production, 2000–2014","interactions":[],"lastModifiedDate":"2016-02-02T13:22:21","indexId":"fs20153079","displayToPublicDate":"2015-12-10T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3079","title":"Shift in Global Tantalum Mine Production, 2000–2014","docAbstract":"Tantalum has a unique set of properties that make it useful in a number of diverse applications. The ability of the metal to store and release electrical energy makes it ideally suited for use in certain types of capacitors that are widely used in modern electronics. Approximately 60 percent of global tantalum consumption is in the electronics industry. The ductility and corrosion resistance of the metal lends itself to application in the chemical processing industry, and its high melting point and high strength retention at elevated temperatures make it an important component of super alloys used in aircraft engines.
\nAs a major industrialized nation, the United States is a leading consumer of tantalum and tantalum-containing products. Domestic deposits typically are of low grade, and no tantalum has been recovered from mining activities in the United States since 1959. Consequently, the United States is nearly completely reliant on imports to meet its domestic consumption of tantalum for economic and national security needs. The recovery of tantalum from mine production is economically viable in only a few countries.
\nAlthough developed countries dominated tantalum mine production in the early 2000s, production today is dominated by countries in the Great Lakes Region of Africa. There is concern that the sales of minerals, including columbite-tantalite or “coltan,” a mineral from which tantalum is derived, have helped finance rebel groups accused of violating human rights as part of the continuing armed conflict in the Democratic Republic of the Congo (DRC) and neighboring countries. These accusations have prompted the passage of legislation in the United States to curb the procurement of these mineral commodities, referred to as “conflict minerals,” from the DRC. Specifically, section 1502 of the 2010 Dodd-Frank Wall Street Reform and Consumer Protection Act (Public Law 111–203, 124 Stat. 2213–2218) requires companies that source tantalum, tin, tungsten, and gold (3TG) to perform due diligence on their supply chains to determine if the materials they use originate from the DRC or adjoining countries (defined as sharing a border with the DRC).
\nThe DRC, Rwanda, and surrounding countries are not globally significant sources of tin, tungsten, or gold, accounting for only about 2 percent of the mined world supply for each of these elements. The region has, however, evolved to become the world’s largest producer of mined tantalum.
\nA further complication of the production of tantalum stems from the opacity of the tantalum market. Unlike most base and precious metals, tantalum concentrates are not publicly traded through commodities exchanges but are bought and sold through networks of dealers and on contract between producers and consumers, some of whom may not provide accurate statistical data concerning the amounts, origins, and destination of the concentrates. Some price data can be found in trade journals or in other publications; however, there are no recognized official set exchange prices for either concentrate or tantalum metal. Because price is determined by negotiation between buyer and seller, published prices for concentrate are probably not representative of global prices paid for concentrate. The development of a mine-to-market supply-chain analysis is complicated and difficult because many of the industry participants that produce, trade, and consume tantalum do not publish statistical information, contracts are long term between miners and buyers, and much of the industry is vertically integrated.
\nAs a result of these and other considerations, tantalum is considered by many to be a “critical” commodity. This fact sheet identifies and addresses the major geographic shifts in the source of mine production of tantalum which have occurred over the past 15 years, some of the factors that drove this shift, and some of the related consequences.
\nOne of the activities of the U.S. Geological Survey National Minerals Information Center (USGS-NMIC) is to analyze global supply chains and characterize major components of mineral and material flows from ore extraction through processing to first tier products. These analyses support the core mission of the USGS-NMIC as the Federal entity responsible for the collection, analysis, and dissemination of objective, unbiased, factual information on minerals essential to the U.S. economy and national security.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153079","usgsCitation":"Bleiwas, D.I., Papp, J.F., and Yager, T.R., 2015, Shift in global tantalum mine production, 2000–2014: U.S. Geological Survey Fact Sheet 2015–3079, 6 p., https://dx.doi.org/10.3133/fs20153079.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070022","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":312092,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3079/fs20153079.pdf","text":"Report","size":"469 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3079"},{"id":312091,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3079/coverthb.jpg"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
Or visit the USGS Minerals Information Web site at http://minerals.usgs.gov/minerals/
","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2015-12-10","noUsgsAuthors":false,"publicationDate":"2015-12-10","publicationStatus":"PW","scienceBaseUri":"566aa23ee4b09cfe53ca44df","contributors":{"authors":[{"text":"Bleiwas, Donald I. bleiwas@usgs.gov","contributorId":1434,"corporation":false,"usgs":true,"family":"Bleiwas","given":"Donald","email":"bleiwas@usgs.gov","middleInitial":"I.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":579900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Papp, John F. jpapp@usgs.gov","contributorId":2895,"corporation":false,"usgs":true,"family":"Papp","given":"John","email":"jpapp@usgs.gov","middleInitial":"F.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":579901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yager, Thomas R. tyager@usgs.gov","contributorId":499,"corporation":false,"usgs":true,"family":"Yager","given":"Thomas","email":"tyager@usgs.gov","middleInitial":"R.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":579902,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160084,"text":"70160084 - 2015 - A new method to generate a high-resolution global distribution map of lake chlorophyll","interactions":[],"lastModifiedDate":"2015-12-10T13:35:13","indexId":"70160084","displayToPublicDate":"2015-12-10T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"A new method to generate a high-resolution global distribution map of lake chlorophyll","docAbstract":"A new method was developed, evaluated, and applied to generate a global dataset of growing-season chlorophyll-a (chl) concentrations in 2011 for freshwater lakes. Chl observations from freshwater lakes are valuable for estimating lake productivity as well as assessing the role that these lakes play in carbon budgets. The standard 4 km NASA OceanColor L3 chlorophyll concentration products generated from MODIS and MERIS sensor data are not sufficiently representative of global chl values because these can only resolve larger lakes, which generally have lower chl concentrations than lakes of smaller surface area. Our new methodology utilizes the 300 m-resolution MERIS full-resolution full-swath (FRS) global dataset as input and does not rely on the land mask used to generate standard NASA products, which masks many lakes that are otherwise resolvable in MERIS imagery. The new method produced chl concentration values for 78,938 and 1,074 lakes in the northern and southern hemispheres, respectively. The mean chl for lakes visible in the MERIS composite was 19.2 ± 19.2, the median was 13.3, and the interquartile range was 3.90–28.6 mg m−3. The accuracy of the MERIS-derived values was assessed by comparison with temporally near-coincident and globally distributed in situmeasurements from the literature (n = 185, RMSE = 9.39, R2 = 0.72). This represents the first global-scale dataset of satellite-derived chl estimates for medium to large lakes.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2015.1029099","usgsCitation":"Sayers, M., Grimm, A.G., Shuchman, R.A., Deines, A., Bunnell, D., Raymer, Z., Rogers, M.W., Woelmer, W., Bennion, D., Brooks, C., Whitley, M.A., Warner, D.M., and Mychek-Londer, J., 2015, A new method to generate a high-resolution global distribution map of lake chlorophyll: International Journal of Remote Sensing, v. 36, no. 7, p. 1942-1964, https://doi.org/10.1080/01431161.2015.1029099.","productDescription":"23 p.","startPage":"1942","endPage":"1964","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062466","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471569,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/01431161.2015.1029099","text":"Publisher Index 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M.","affiliations":[],"preferred":false,"id":581807,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bunnell, David B. dbunnell@usgs.gov","contributorId":141167,"corporation":false,"usgs":true,"family":"Bunnell","given":"David B.","email":"dbunnell@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":581803,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Raymer, Zachary B","contributorId":150484,"corporation":false,"usgs":false,"family":"Raymer","given":"Zachary B","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":581808,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rogers, Mark W. 0000-0001-7205-5623 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dmwarner@usgs.gov","orcid":"https://orcid.org/0000-0003-4939-5368","contributorId":2986,"corporation":false,"usgs":true,"family":"Warner","given":"David","email":"dmwarner@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":581814,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Mychek-Londer, Justin G.","contributorId":64138,"corporation":false,"usgs":true,"family":"Mychek-Londer","given":"Justin G.","affiliations":[],"preferred":false,"id":581815,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70159058,"text":"ds967 - 2015 - Hydrologic data for the Walker River Basin, Nevada and California, water years 2010–14","interactions":[],"lastModifiedDate":"2015-12-10T10:32:26","indexId":"ds967","displayToPublicDate":"2015-12-10T08:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"967","title":"Hydrologic data for the Walker River Basin, Nevada and California, water years 2010–14","docAbstract":"Walker Lake is a threatened and federally protected desert terminal lake in western Nevada. To help protect the desert terminal lake and the surrounding watershed, the Bureau of Reclamation and U.S. Geological Survey have been studying the hydrology of the Walker River Basin in Nevada and California since 2004. Hydrologic data collected for this study during water years 2010 through 2014 included groundwater levels, surface-water discharge, water chemistry, and meteorological data. Groundwater levels were measured in wells, and surface-water discharge was measured in streams, canals, and ditches. Water samples for chemical analyses were collected from wells, streams, springs, and Walker Lake. Chemical analyses included determining physical properties; the concentrations of major ions, nutrients, trace metals, dissolved gases, and radionuclides; and ratios of the stable isotopes of hydrogen and oxygen. Walker Lake water properties and meteorological parameters were monitored from a floating platform on the lake. Data collection methods followed established U.S. Geological Survey guidelines, and all data are stored in the National Water Information System database. All of the data are presented in this report and accessible on the internet, except multiple-depth Walker Lake water-chemistry data, which are available only in this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds967","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Pavelko, Michael T., and Orozco, Erin L., 2015, Hydrologic data for the Walker River Basin, Nevada and California, water years 2010–14: U.S. Geological Survey Data Series 967, 17 p., plus appendixes, https://dx.doi.org/10.3133/ds967.","productDescription":"Report: iv, 17 p.; 6 Appendixes","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2009-10-01","temporalEnd":"2014-09-30","ipdsId":"IP-065428","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":311927,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0967/ds967_appendix06.xlsx","text":"Appendix 6","size":"3.3 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 967 Appendix 6","linkHelpText":"Lake water-chemistry and meteorological data from sites located on Walker Lake, water years 2011–14."},{"id":311920,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0967/coverthb.jpg"},{"id":311922,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0967/ds967_appendix01.xlsx","text":"Appendix 1","size":"156 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 967 Appendix 1","linkHelpText":"Water-level measurements for the Walker River Basin study, water years 2010–14."},{"id":311919,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0967/ds967.pdf","text":"Report","size":"2.5 MB","description":"DS 967 PDF"},{"id":311923,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0967/ds967_appendix02.xlsx","text":"Appendix 2","size":"20 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 967 Appendix 2","linkHelpText":"Surface-water discharge measurements for the Walker River Basin study, water years 2011–13."},{"id":311924,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0967/ds967_appendix03.xlsx","text":"Appendix 3","size":"56 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 967 Appendix 3","linkHelpText":"Groundwater-chemistry data for the Walker River Basin study, water years 2010–12."},{"id":311926,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0967/ds967_appendix05.xlsx","text":"Appendix 5","size":"19 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 967 Appendix 5","linkHelpText":"Spring water-chemistry data for the Walker River Basin study, water years 2010–13."},{"id":311925,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0967/ds967_appendix04.xlsx","text":"Appendix 4","size":"40 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 967 Appendix 4","linkHelpText":"Stream water-chemistry data for the Walker River Basin study, water years 2011–13."}],"country":"United States","state":"California, Nevada","otherGeospatial":"Walker River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.22912597656249,\n 38.026458711461245\n ],\n [\n -118.98193359375,\n 38.1734326790354\n ],\n [\n -118.8006591796875,\n 38.24249456800328\n ],\n [\n -118.6138916015625,\n 38.29424797320529\n ],\n [\n -118.48205566406251,\n 38.182068998322094\n ],\n [\n -118.55895996093749,\n 38.06539235133249\n ],\n [\n -118.54248046874999,\n 37.97884504049713\n ],\n [\n -118.38317871093749,\n 38.02213147353745\n ],\n [\n -118.26232910156249,\n 38.16479533621134\n ],\n [\n -118.23486328125,\n 38.29424797320529\n ],\n [\n -118.35571289062499,\n 38.638327308061875\n ],\n [\n -118.4381103515625,\n 38.70265930723801\n ],\n [\n -118.5150146484375,\n 38.839707613545144\n ],\n [\n -118.46557617187499,\n 38.950865400919994\n ],\n [\n -118.487548828125,\n 39.02345139405932\n ],\n [\n -118.63037109375,\n 39.027718840211605\n ],\n [\n -118.828125,\n 39.08743603215884\n ],\n [\n -118.9544677734375,\n 39.142842478062505\n ],\n [\n -119.11376953125,\n 39.1854331703021\n ],\n [\n -119.24560546875001,\n 39.1854331703021\n ],\n [\n -119.44335937499999,\n 39.104488809440475\n ],\n [\n -119.54223632812501,\n 38.96795115401593\n ],\n [\n -119.608154296875,\n 38.796908303484294\n ],\n [\n -119.65209960937501,\n 38.732661120482334\n ],\n [\n -119.7344970703125,\n 38.61257832462118\n ],\n [\n -119.6685791015625,\n 38.5008925889646\n ],\n [\n -119.63562011718751,\n 38.40194908237825\n ],\n [\n -119.63012695312499,\n 38.190704293996504\n ],\n [\n -119.60266113281249,\n 38.06971703320484\n ],\n [\n -119.4049072265625,\n 38.0091482264894\n ],\n [\n -119.2950439453125,\n 37.97018468810549\n ],\n [\n -119.22912597656249,\n 38.026458711461245\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
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2730 N. Deer Run Rd.
Carson City, NV 89701
http://nevada.usgs.gov/water/